Breast milk is the optimal natural food for newborns. However， some newborns cannot receive maternal breast milk due to reasons such as mother-infant separation or insufficient lactation. The establishment of human milk banks （HMB） can effectively address these issues， thereby increasing the breastfeeding rate among hospitalized newborns and improving their quality of survival. However， HMB in China is still in the development and improvement stage. Its implementation involves a series of ethical issues， such as informed consent， privacy protection， economic incentives， quality and safety， and fair resource distribution， which hinder HMB’s widespread promotion. Therefore， discussing the ethical dilemmas faced by the widespread establishment of HMB in China’s hospitals and analyzing coping strategies are crucial for improving the breastfeeding rate of newborns. This paper deeply analyzed and sorted out the ethical issues and challenges currently faced by HMB in China， and proposed corresponding strategies， including “ensuring informed consent and voluntary participation of both donors and recipients，” “protecting the privacy of donors and recipients，” “establishing an ethics-based moral incentive and social support system，” “strictly controlling quality and safety issues”， and “developing fair and rational policies，” aiming to provide a reference solution for addressing ethical concerns in the establishment and operation of HMB.

Objective: To explore the relationship between sedentary behavior with cardiorespiratory fitness and executive function in adolescents, and to provide some references for sedentary behavior prevention and executive function improvement. Methods: From September to December 2022, a total of 5 018 adolescents aged 13 to 18 years were selected by stratified random sampling method in Shanghai, Suzhou, Taiyuan,Wuyuan, Xingyi, and Urumqi to conduct physical activity survey, as well as cardiorespiratory fitness and executive function assessment. Pearson s correlation was used to analyze the relationship between sedentary behavior, cardiorespiratory fitness and executive function. The mediation effect model was fitted by the bootstrap mediation procedure in the PROCESS (version 3.3 ) SPSS macro compiled by Haves, and the mediation effect of adolescents cardiorespiratory fitness in the relationship between static behavior and executive function was examined using model 4 in the PROCESS SPSS macro, where Boosrap method was used to compute the mediation effect of adolescents cardiorespiratory fitness. where the Boosrap method was used to calculate confidence intervals for the mediating effects. Results: Adolescents daily sedentary time was positively correlated with both the refreshing function (1-back and 2-back) and the switch function reaction time ( r =0.05, 0.07, 0.05, P <0.01). Adolescent VO 2max was negatively correlated with both the refreshing function (1-back,2-back) and the switching function ( r =-0.09, -0.14 , -0.11, P <0.01). Adolescents daily sedentary time was negatively correlated with VO 2max ( r =-0.04, P <0.01); cardiorespiratory fitness mediated effect values between sedentary behavior and refreshing function (1-back and 2-back) and converted function were 0.20(95% CI =0.06-0.36), 0.43(95% CI =0.14-0.74) and 0.13 (95% CI =0.04-0.22), with mediating effect shares of 6.87%, 8.33% and 8.59%, respectively. Conclusion The duration of sedentary behavior in adolescents is related to executive function performance, and cardiorespiratory fitness may serve as a mediator to mediate the association between sedentary behavior and executive function in adolescents.

Objective To explore the influencing factors of rational perioperative drug use,and to establish a rationality prediction model based on machine learning to assist pharmacists in prescription review.Methods A retrospective analysis was conducted on the perioperative prescription data of neurosurgery patients from a tertiary hospital and a central hospital in Shanxi Province between March 2021 and March 2023.Univariate analysis and multivariate Logistic regression were initially used to identify factors influencing rational drug use,followed by Lasso regression and multicollinearity analysis to select important variables.The data was split into a training set and test set at a ratio of 7∶3,and decision tree(DT),multi-layer perceptron(MLP),extreme gradient boosting(XGBoost),support vector machine(SVM),and random forest(RF)learning models were constructed.Results A total of 1 500 prescriptions were included,of which 668 were classified as rational and 832 as irrational.In both the training and test sets,the AUC values of the DT,XGBoost,and RF models exceeded 0.9.The DT model showed the highest sensitivity(0.81),while the RF model demonstrated the highest specificity(0.90).In the RF model,the number of comorbidities,preoperative waiting time,total hospitalization cost,prescribing physician's title,and adverse reaction occurrence negatively impacted prescription rationality,whereas the number of drugs,age,and administration route positively influenced rationality.Conclusion The machine learning-based rational drug use prediction model demonstrates strong predictive performance,effectively assisting pharmacists in prescription review and helping to reduce the incidence of irrational drug use.

China has classified the Corona Virus Disease 2019(COVID-19) as a statutory category B infectious disease and managed it according to Category B since January 8, 2023.In view that Omicron variant is currently the main epidemic strain in China, in order to guide the treatment of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) infection in children with the times, refer to the Diagnosis and Treatment Protocol for Novel Coronavirus Infection (Trial 10 th Edition), Expert Consensus on Diagnosis, Treatment and Prevention of Novel Coronavirus Infection in Children (Fourth Edition) and the Diagnosis and Treatment Strategy for Pediatric Related Viral Infections.The Expert Consensus on the Diagnosis, Treatment and Prevention of Novel Coronavirus Infection in Children (Fifth Edition) has been formulated and updated accordingly on related etiology, epidemiology, pathogenic mechanism, clinical manifestations, auxiliary examination, diagnosis and treatment, and added key points for the treatment of COVID-19 related encephalopathy, fulminating myocarditis and other serious complications for clinical reference.

Objective:To explore the feasibility of low-dose 4DCT scanning in simulation and target delineation for solitary pulmonary tumors (SPTs).Methods:23 patients with SPTs received 4DCT scanning simulation with the conventional scanning (CON), low voltage (LV), low current (LA) and low voltage combined with low current (LVA) in sequence. Based on the 4DCT images derived from the four sets of scanning parameters, the internal gross tumor volume (IGTV CON, IGTV V, IGTV A, IGTV VA) of SPTs were delineated and matched. Taking IGTV CON as reference, the tumor displacement and the centroid position of IGTV V, IGTV A and IGTV VA were compared with IGTV CON. The radiation doses under different scanning parameters were compared. Results:The volumes of IGTV CON, IGTV V and IGTV A were (12.26±12.30) cm 3, (12.21±12.16) cm 3 and (11.87±11.70) cm 3, respectively ( P=0.337). IGTV VA was (11.34±11.07) cm 3, significantly smaller than IGTV CON ( P=0.005). There was no significant difference in the centroid positions of IGTV CON, IGTV V, IGTV A and IGTV VA in three directions ( P=0.491, 0.360, 0.136). The Dice′s similarity coefficient (DSC VA) was significantly lower than DSC V and DSC A ( P=0.004, 0.030). The tumor displacement measured by the four sets of 4DCT images was similar in the LR direction ( P=0.470), and also in the AP direction ( P=0.108). For the displacement in the SI direction, LVA scanning was smaller than CON ( P=0.015). The radiation doses under four different scanning conditions were (397.0±140.3) mGy·cm, (175.0±61.8) mGy·cm, (264.8±95.3) mGy·cm and (116.8±41.2) mGy·cm, respectively ( P<0.001). Conclusions:LV or LA scanning exert no significant effect on the volume, centroid position of IGTV and the tumor displacement in 4DCT simulation for SPTs. The radiation dose that patients receive under LV and LV scanning is lower than that of CON. Consequently, LV or LA scanning is feasible in 4DCT simulation and target delineation for SPTs.

Monkeypox is a zoonotic disease.Previous studies have shown that children are vulnerable to monkeypox and are also at high risk for severe disease or complications.In order to improve pediatricians′ understanding of monkeypox and achieve early detection, early diagnosis, early treatment and early disposal, the committee composed of more than 40 experts in the related fields of infectious diseases, pediatrics, infection control and public health formulate this expert consensus, on the basis of the latest clinical management and infection prevention and control for monkeypox released by the World Health Organization (WHO), the guidelines for diagnosis and treatment of monkeypox (version 2022) issued by National Health Commission of the People′s Republic of China and other relevant documents.During the development of this consensus, multidisciplinary experts have repeatedly demonstrated the etiology, epidemiology, transmission, clinical manifestations, laboratory examinations, diagnosis and differential diagnosis, treatment, discharge criteria, prevention, case management process and key points of prevention and control about monkeypox.

Since December 2019, severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) infections have raged globally for more than 2 years.China has always adopted scientific and effective prevention and control measures to achieved some success.However, with the continuous variation of SARS-CoV-2 cases and imported cases from abroad, the prevention and control work has become more difficult and complex.With the variation of the mutant strain, the number of cases in children changed, and some new special symptoms and complications were found, which proposed a new topic for the prevention and treatment of SARS-CoV-2 infection in children in China.Based on the third edition, the present consensus according to the characteristics of the new strain, expounded the etiology, pathology, pathogenesis, and according to the clinical characteristics and experience of children′s cases, and puts forward recommendations on the diagnostic criteria, laboratory examination, treatment, prevention and control of children′s cases for providing reference for further guidance of effective prevention and treatment of SARS-CoV-2 infection in children in China.

Objective: To determine the spatiotemporal distribution of Schistosoma (S.) japonicum infections in humans, livestock, and Oncomelania (O.) hupensis across the endemic foci of China. Methods: Based on multi-stage continuous downscaling of sentinel monitoring, county-based schistosomiasis surveillance data were captured from the national schistosomiasis surveillance sites of China from 2005 to 2019. The data included S. japonicum infections in humans, livestock, and O. hupensis. The spatiotemporal trends for schistosomiasis were detected using a Joinpoint regression model, with a standard deviational ellipse (SDE) tool, which determined the central tendency and dispersion in the spatial distribution of schistosomiasis. Further, more spatiotemporal clusters of S. japonicum infections in humans, livestock, and O. hupensis were evaluated by the Poisson model. Results: The prevalence of S. japonicum human infections decreased from 2.06% to zero based on data of the national schistosomiasis surveillance sites of China from 2005 to 2019, with a reduction from 9.42% to zero for the prevalence of S. japonicum infections in livestock, and from 0.26% to zero for the prevalence of S. japonicum infections in O. hupensis. Analysis using an SDE tool showed that schistosomiasis-affected regions were reduced yearly from 2005 to 2014 in the endemic provinces of Hunan, Hubei, Jiangxi, and Anhui, as well as in the Poyang and Dongting Lake regions. Poisson model revealed 11 clusters of S. japonicum human infections, six clusters of S. japonicum infections in livestock, and nine clusters of S. japonicum infections in O. hupensis. The clusters of human infection were highly consistent with clusters of S. japonicum infections in livestock and O. hupensis. They were in the 5 provinces of Hunan, Hubei, Jiangxi, Anhui, and Jiangsu, as well as along the middle and lower reaches of the Yangtze River. Humans, livestock, and O. hupensis infections with S. japonicum were mainly concentrated in the north of the Hunan Province, south of the Hubei Province, north of the Jiangxi Province, and southwestern portion of Anhui Province. In the 2 mountainous provinces of Sichuan and Yunnan, human, livestock, and O. hupensis infections with S. japonicum were mainly concentrated in the northwestern portion of the Yunnan Province, the Daliangshan area in the south of Sichuan Province, and the hilly regions in the middle of Sichuan Province. Conclusions: A remarkable decline in the disease prevalence of S. japonicum infection was observed in endemic schistosomiasis in China between 2005 and 2019. However, there remains a long-term risk of transmission in local areas, with the highest-risk areas primarily in Poyang Lake and Dongting Lake regions, requiring to focus on vigilance against the rebound of the epidemic. Development of high-sensitivity detection methods and integrating the transmission links such as human and livestock infection, wild animal infection, and O. hupensis into the surveillance-response system will ensure the elimination of schistosomiasis in China by 2030.

Sleep apnea (SA) detection method based on traditional machine learning needs a lot of efforts in feature engineering and classifier design. We constructed a one-dimensional convolutional neural network (CNN) model, which consists in four convolution layers, four pooling layers, two full connection layers and one classification layer. The automatic feature extraction and classification were realized by the structure of the proposed CNN model. The model was verified by the whole night single-channel sleep electrocardiogram (ECG) signals of 70 subjects from the Apnea-ECG dataset. Our results showed that the accuracy of per-segment SA detection was ranged from 80.1% to 88.0%, using the input signals of single-channel ECG signal, RR interval (RRI) sequence, R peak sequence and RRI sequence + R peak sequence respectively. These results indicated that the proposed CNN model was effective and can automatically extract and classify features from the original single-channel ECG signal or its derived signal RRI and R peak sequence. When the input signals were RRI sequence + R peak sequence, the CNN model achieved the best performance. The accuracy, sensitivity and specificity of per-segment SA detection were 88.0%, 85.1% and 89.9%, respectively. And the accuracy of per-recording SA diagnosis was 100%. These findings indicated that the proposed method can effectively improve the accuracy and robustness of SA detection and outperform the methods reported in recent years. The proposed CNN model can be applied to portable screening diagnosis equipment for SA with remote server.
Electrocardiography ; Humans ; Machine Learning ; Neural Networks, Computer ; Sensitivity and Specificity ; Sleep Apnea Syndromes/diagnosis*

Objective:To evaluate the prognostic value of extravascular lung water index (EVLWI) , soluble intercellular adhesion molecule-1(sICAM-1) and Krebs yon den lungen-6 (KL-6) in severe pneumonia patients with Severe Acute Respiratory Syndrome (ARDS).Methods:A prospective study was conducted in Respiratory Intensive Care Unit of the Affiliated Zhengzhou Central Hospital of Zhengzhou University from October 2017 to February 2020. The study included 65 severe pneumonia patients with ARDS, who was performed by measurement of pulse index continuous cardiac output and survived more than 3days after admission. The Extravascular Lung Water Index (EVLWI) , sICAM-1, KL-6 and Oxygenation Index(OI) on 1st, 3rd and 5th day were detected. APACHEⅡ score, patient survival events (days) and survival outcome were recorded. Correlation analysis between EVLWI, sICAM-1, KL-6 and OI was performed on the 1st, 3rd and 5th day after admission. Independent risk factors of mortality in severe pneumonia patients with ARDS were analyzed by multiple logistic regression. Receiver operating characteristic curve was drawn, and the prognostic value of each parameter was assessed finally.Results:The PCT, EVLWI, sICAM-1, KL-6 and APACHEⅡ score in the death group were significantly higher than those in the survival group ( P<0.05) at RICU admission, and the length of RICU stay was significantly shorter than that in the survival group ( P<0.05), while differences in other clinical characteristics between two groups were not statistically significant ( P>0.05) . These parameters including levels of EVLWI, sICAM-1, KL-6, Procalcitonin and APACHE Ⅱscore in the death group were significantly higher than those in the survival group on the 1st, 3rd and 5th day ( P<0.05), whereas the OI was significantly lower than that of the survival group on the 3rd and 5th day ( P<0.05). Logistic regression analysis showed that EVLWI, sICAM-1, KL-6 level were significantly related with the mortality of these patients. The levels of sICAM-1, kl-6 and EVLWI on 1st, 3rd and 5th day after RICU admission showed a significant negative correlation with OI ( P<0.001). Whereas, The levels of sICAM-1, kL-6 on 1st, 3rd and 5th day showed a significant positive correlation with EVLWI ( P<0.001). The sensitivity and specificity of sICAM-1, KL-6 combined with EVLWI in prognosis evaluation on 1st, 3rd and 5th day were 75.0%, 84.4%, 85.0%, 66.7%, 80.0%, 86.7%, respectively. The AUC was 0.864, 0.881, 0.892 on 1st, 3rd and 5th day, respectively ( P<0.001), which had a better prognostic value than each of them. Conclusions:EVLWI, sICAM-1 and KL-6 were independent risk factors for the prognosis of severe pneumonia patients with ARDS. The combination of EVLWI, sICAM-1 and KL-6 might be important in early predicting the prognosis of the 28d mortality.